﻿<?xml version="1.0" encoding="utf-8"?>
<ArticleSet>
  <ARTICLE>
    <Journal>
      <PublisherName>مرکز منطقه ای اطلاع رسانی علوم و فناوری</PublisherName>
      <JournalTitle>Journal of Information Systems and Telecommunication (JIST) </JournalTitle>
      <ISSN>2322-1437</ISSN>
      <Volume>9</Volume>
      <Issue>33</Issue>
      <PubDate PubStatus="epublish">
        <Year>2021</Year>
        <Month>4</Month>
        <Day>12</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Denoising and Enhancement Speech Signal Using Wavelet</ArticleTitle>
    <VernacularTitle>Denoising and Enhancement Speech Signal Using Wavelet</VernacularTitle>
    <FirstPage>37</FirstPage>
    <LastPage>44</LastPage>
    <ELocationID EIdType="doi">10.52547/jist.9.33.37</ELocationID>
    <Language>en</Language>
    <AuthorList>
      <Author>
        <FirstName>Meriane</FirstName>
        <LastName>Brahim</LastName>
        <Affiliation>University of  Batna 2 (UB2)</Affiliation>
      </Author>
    </AuthorList>
    <History PubStatus="received">
      <Year>2020</Year>
      <Month>10</Month>
      <Day>28</Day>
    </History>
    <Abstract>Speech enhancement aims to improve the quality and intelligibility of speech using various techniques and algorithms. The speech signal is always accompanied by background noise. The speech and communication processing systems must apply effective noise reduction techniques in order to extract the desired speech signal from its corrupted speech signal. In this project we study wavelet and wavelet transform, and the possibility of its employment in the processing and analysis of the speech signal in order to enhance the signal and remove noise of it. We will present different algorithms that depend on the wavelet transform and the mechanism to apply them in order to get rid of noise in the speech, and compare the results of the application of these algorithms with some traditional algorithms that are used to enhance the speech. The basic principles of the wavelike transform are presented as an alternative to the Fourier transform. Or immediate switching of the window The practical results obtained are based on processing a large database dedicated to speech bookmarks polluted with various noises in many SNRs. This article tends to be an extension of practical research to improve speech signal for hearing aid purposes. Also learn about the main frequency of letters and their uses in intelligent systems, such as voice control systems.</Abstract>
    <ObjectList>
      <Object Type="Keyword">
        <Param Name="Value">Wavelet Transform; Speech Enhancement</Param>
      </Object>
      <Object Type="Keyword">
        <Param Name="Value">Denoising</Param>
      </Object>
      <Object Type="Keyword">
        <Param Name="Value">Discrete Wavelet Ttransforms (DWT)</Param>
      </Object>
      <Object Type="Keyword">
        <Param Name="Value">Noise Reduction in Speech Signals.</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="Pdf">http://jist.ir/en/Article/Download/15616</ArchiveCopySource>
  </ARTICLE>
</ArticleSet>